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lambdar's Introduction

Hi there πŸ‘‹ 🦊

I'm a data engineer based in Wellington, New Zealand. I mostly write R and Python but have dabbled in a few different things over the years.

Stuff I made

I maintain some open source R packages:

  • 🍦 icecream makes print debugging a little sweeter.
  • πŸ›Έ levitate does fuzzy string comparison.
  • πŸ•ΈοΈ foodwebr draws function dependency graphs.
  • Ξ» lambdar helps you run R on AWS Lambda.

Please try them out! If you want to contribute code or feedback that would be awesome ⭐

Stuff I'm learning

Stuff I write

I sometimes blog at lewinfox.com.

lambdar's People

Contributors

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lambdar's Issues

Allow multiple lambda functions per project

Because we can specify the handler when running the container (docker run <image> filename.function_name) there's no reason not to allow multiple instances of the same container, each running a different function. Saves building multiple different images.

Auto-detect `@lamba` tags

When generating _lambdar.yml, look for @lambda tags and populate the YAML with the right file.function handler.

There should only be one @lamba tag per project - check and handle this.

Use `callr::r()` to isolate lambda calls

In the lambda_runtime.R we can use

  response_object <- withCallingHandlers(
    {
      res <- list(
        result = NULL,
        status = "ok"
      )

      lambda_function <- match.fun(function_name)
      res$result <- callr::r(lambda_function, args = event_content)
      res
    },
  # ...

to run the lambda in a separate subprocess. We still get errors back but we lose visibility of warnings. Is this desirable? Given that we're not doing much with warnings is this an acceptable tradeoff for extra safety?

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